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E-raamat: Intelligent Cities: Enabling Tools and Technology

(IBM Pvt.Ltd., Manyata Tech Park, Bangolore, India), (IBM Pvt.Ltd., Manyata Tech Park, Bangolore, India)
  • Formaat: 520 pages
  • Ilmumisaeg: 15-Jun-2015
  • Kirjastus: Apple Academic Press Inc.
  • Keel: eng
  • ISBN-13: 9781040076941
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Intelligent Cities: Enabling Tools and TechnologySuurem pilt
  • Formaat: 520 pages
  • Ilmumisaeg: 15-Jun-2015
  • Kirjastus: Apple Academic Press Inc.
  • Keel: eng
  • ISBN-13: 9781040076941
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The emergence of highly promising and potent technologies has enabled the transition of ordinary objects into smart artifacts—providing wider connectivity of digitized entities that can facilitate the building of connected cities. This book provides readers with a solid foundation on the latest technologies and tools required to develop and enhance smart cities around the world.

The book begins by examining the rise of the cloud as the fundamental technology for establishing and sustaining smart cities and enterprises. Explaining the principal technologies and platform solutions for implementing intelligent cities, the book details the role of various technologies, standards, protocols, and tools in establishing flexible homes and the buildings of the future.

  • Examines IT platforms and tools from various product vendors
  • Considers service-oriented architecture and event-driven architecture for smart city applications
  • Explains how to leverage big data analytics for smart city enhancement and improved decision making
  • Includes case studies of intelligent cities, smart homes, buildings, transports, healthcare systems, and airports

The authors explore the convergence of cloud computing and enterprise architecture and present valuable information on next-generation cloud computing. They also cover the various architectural types, including enterprise-scale integration, security, management, and governance.

The book concludes by explaining the various security requirements of intelligent cities as well as the threats and vulnerabilities of the various components that form the basis of the intelligent city framework, including cloud, big data, Internet of Things, and mobile technologies.

Arvustused

In this book, the authors have presented a large number of right and relevant details on realizing and sustaining intelligent cities (the system of systems) across the world. ... this book will be informative and inspiring for readers, especially business executives, technical experts, solution architects, city planners and consultants, and government officials. The book has been designed and developed to be comprehensive and compact in explaining the nitty-gritty of promising smart city technologies, IT solutions, and use cases.Sandesh Bhat, Vice President, India Software Labs, IBM

Foreword xix
Preface xxiii
Acknowledgments xxvii
Chapter 1 Envisioning Intelligent Cities 1(40)
1.1 Introduction
2(1)
1.2 Unfolding the Smarter Planet Vision
2(2)
1.3 The Need for Intelligent Cities
4(2)
1.4 City-Specific Challenges
6(2)
1.4.1 Trickling Urbanization Challenges
6(2)
1.5 The Vast Potentials of Smart Cities
8(1)
1.6 City Transformation Strategy
8(9)
1.6.1 Infrastructure Optimization
9(1)
1.6.2 System Infrastructure
9(1)
1.6.3 The Adoption of Versatile Technologies
10(2)
1.6.4 The Assimilation of Architectures
12(1)
1.6.5 Services Are Everywhere
13(1)
1.6.6 Devices Are Connected and Cyber-Enabled for People-Centric Services
14(1)
1.6.7 Process Excellence
15(2)
1.6.7.1 Monitoring and Management of City Processes
16(1)
1.6.7.2 Process Management
16(1)
1.6.8 Make Sense Out of Data for Big Insights
17(1)
1.7 The Key Trends in IT toward Smart Cities
17(12)
1.7.1 The Shift toward People IT
17(1)
1.7.2 The Era of Smart Computing
18(1)
1.7.3 Smarter Environments
19(1)
1.7.4 The Need for Cloud-Enablement
20(1)
1.7.5 A Few Smart City Use Cases
21(8)
1.7.5.1 Smart Homes
22(2)
1.7.5.2 Security and Surveillance
24(1)
1.7.5.3 Remote Asset Management
24(1)
1.7.5.4 Connected Goods
24(1)
1.7.5.5 Connected Consumer Electronics
25(1)
1.7.5.6 Other Potential Uses
26(3)
1.8 Smart City Infrastructure and Platform Solutions
29(7)
1.8.1 Smart City Infrastructures
29(2)
1.8.2 Leading Smart City Platforms
31(5)
1.8.2.1 IBM Intelligent Operations Center
31(2)
1.8.2.2 Oracle Smart City Platform
33(1)
1.8.2.3 The Thales Hypervisor Supervision System
34(2)
1.9 The Context-Aware Framework for Smart City Applications
36(3)
1.9.1 Data Collection and Cleansing
36(1)
1.9.2 Data Storage
37(1)
1.9.3 Data Interpretation
37(1)
1.9.4 Cloud-Based
38(1)
1.9.5 Data Dissemination
38(1)
1.10 Conclusion
39(1)
References
40(1)
Chapter 2 Mobile Technologies And Applications For Intelligent Cities 41(38)
2.1 Introduction
43(4)
2.2 Evolution of Mobile Wireless Technologies
47(2)
2.3 Mobile Application Development Platforms
49(3)
2.4 Challenges of Intelligent Cities and Solutions Offered by Mobile Wireless Networks and Devices
52(17)
2.4.1 Mobile Payments and Ticketing
53(5)
2.4.1.1 Role of NFC in Mobile eTicketing
55(3)
2.4.2 Intelligent Energy Conservation Using Mobile Devices
58(4)
2.4.2.1 Excessive Growth in Customer Demands
58(1)
2.4.2.2 Increase in Infrastructure Cost
58(1)
2.4.2.3 Regulations Imposed by Government Rules
58(4)
2.4.3 Analysis and Commercial Insights
62(1)
2.4.4 Drivers for Mobile BI Adoption
62(1)
2.4.5 Key Trends in Mobile BI
62(1)
2.4.6 Steps to Get Started with Mobile BI
63(1)
2.4.7 Mobile Healthcare
64(3)
2.4.7.1 Value Chain for Mobile Heathcare
67(1)
2.4.8 Wireless Fleet Management
67(2)
2.5 Enabling Mobile Technologies for an Intelligent City
69(7)
2.5.1 Mobile Augmented Reality
69(17)
2.5.1.1 MARS in Practice
71(5)
2.6 Conclusion
76(1)
References
77(2)
Chapter 3 The Role And Relevance Of Software-Defined Cloud Infrastructures 79(50)
3.1 Introduction
80(3)
3.2 About Cloud Technology
83(1)
3.3 Key Motivations for Cloud-Enabled Environments
84(1)
3.4 Why Cloud Technology Is Being Aggressively Pursued by Worldwide Governments
85(1)
3.5 A Look at Cloud-Inspired Enterprise Transformations
86(29)
3.5.1 The Emergence of Cloud Environments
87(3)
3.5.2 Energy Optimization
90(1)
3.5.3 Cloud-Enabled and Hosted Smarter City Applications
91(1)
3.5.4 A Cloud-Enabled Context-Aware Framework for Smarter Environments
92(1)
3.5.5 A Sample Use Case
93(1)
3.5.6 Cloud-Based Smarter Home Applications
94(1)
3.5.7 Cloud-Enabled Smart Grids
95(2)
3.5.8 A Cloud-Based Monitoring Framework for Smart Homes
97(1)
3.5.9 Cloud-Inspired Smarter Healthcare Services
98(1)
3.5.10 Sensor-Cloud Integration for Smarter Cities
99(1)
3.5.11 Social and Sensor Data Fusion in Cloud
100(1)
3.5.12 Integrating Sensors with Cloud Using Dynamic Proxies
101(1)
3.5.13 The Next-Generation Hybrid Clouds
102(3)
3.5.14 The Compelling Use Cases for Next-Generation Hybrid Clouds
105(1)
3.5.15 Use Cases-Computation and Actionable Insights
105(2)
3.5.16 Storage Use Cases
107(1)
3.5.17 Data Dissemination
107(1)
3.5.18 Software-Defined Infrastructures and Software-Defined Environments
108(7)
3.5.18.1 Simplified and Synchronized Operations of Cloud Infrastructures through Standard APIs
109(1)
3.5.18.2 Instant-On IT
109(1)
3.5.18.3 Programmable Infrastructures
110(1)
3.5.18.4 Deeper Visibility and Higher Controllability
110(1)
3.5.18.5 Business Continuity
110(1)
3.5.18.6 Enhanced Utilization
111(1)
3.5.18.7 Utility Computing
111(4)
3.6 Building Blocks of Software-Defined Data Centers
115(11)
3.6.1 Software-Defined Networking
115(2)
3.6.2 The Key Motivations for SDN
117(1)
3.6.3 Tending toward Network Virtualization
118(1)
3.6.4 The Need of SDN for the Cloud
119(1)
3.6.5 Software-Defined Storage
120(3)
3.6.6 Cloud-Based Big Data Storage
123(1)
3.6.7 Key Characteristics of Software-Defined Storage
124(8)
3.6.7.1 Commodity Hardware
125(1)
3.6.7.2 Scale-Out Architecture
125(1)
3.6.7.3 Resource Pooling
125(1)
3.6.7.4 Abstraction
125(1)
3.6.7.5 Automation
125(1)
3.6.7.6 Programmability
126(1)
3.7 Conclusion
126(1)
References
127(2)
Chapter 4 Big Data Analytics For Real-Time City Insights 129(48)
4.1 Introduction
130(2)
4.2 Data Analytics and Intelligent Cities
132(8)
4.2.1 The Prominent Sources of Big Data
132(1)
4.2.2 Describing the Big Data World
133(1)
4.2.3 Big Data Characteristics
134(1)
4.2.4 A Perspective on Big Data Computing
135(3)
4.2.5 Why Big Data Computing?
138(1)
4.2.6 The Application Domains
138(2)
4.3 Describing Big Data Analytics
140(6)
4.3.1 The Big Trends of BDA
142(1)
4.3.2 BDA Use Cases
143(9)
4.3.2.1 Customer Satisfaction Analysis
143(1)
4.3.2.2 Market Sentiment Analysis
144(1)
4.3.2.3 Epidemic Analysis
144(1)
4.3.2.4 Using BDA in Healthcare
145(1)
4.4 Machine Data Analytics by Splunk®
146(5)
4.5 Open Data for Next-Generation Cities
151(1)
4.6 Edge Data for Cities of the Future
152(6)
4.6.1 Edge Data for Smarter Cities
154(1)
4.6.2 Edge Data for Smart Retailers
154(1)
4.6.3 Edge Data for Smart Automobiles
155(1)
4.6.4 Edge Data for Smart Manufacturing
156(1)
4.6.5 Edge Data for Facilities and Asset Management
157(1)
4.7 Integrated BDA Platforms
158(9)
4.7.1 Software-Defined Infrastructures for BDA
159(3)
4.7.2 Civitas: The Smart City Middleware
162(2)
4.7.3 Hitachi Smart City Platform
164(1)
4.7.4 Data Collection
165(1)
4.7.5 Data Analysis
166(1)
4.7.6 Application Coordination
166(1)
4.8 BDA Frameworks and Infrastructure
167(7)
4.8.1 Apache Hadoop Software Framework
168(3)
4.8.2 NoSQL Databases
171(3)
4.9 Conclusion
174(1)
References
175(2)
Chapter 5 The Internet Of Things For Connected And Cognitive Cities 177(58)
5.1 Introduction
178(1)
5.2 Envisioning the IoT Era
179(1)
5.3 Emerging IoT Trends
180(12)
5.3.1 Deeper Digitization toward Smart Objects
180(2)
5.3.2 The Growing Device Ecosystem
182(3)
5.3.2.1 Machine-to-Machine (M2M) Integration
184(1)
5.3.3 Software-Defined Cloud Infrastructures
185(6)
5.3.3.1 Cloud-Enabled Embedded Applications
185(2)
5.3.3.2 Cloud Infrastructures for Real- Time Big Data Analytics
187(1)
5.3.3.3 Cloud Infrastructures for Smart Phone Services
188(1)
5.3.3.4 Device-to-Cloud (D2C) Integration
188(1)
5.3.3.5 Cloud-to-Cloud (C2C) Integration
189(1)
5.3.3.6 Sensor-to-Cloud (S2C) Integration
190(1)
5.3.4 Big Data Analytics
191(1)
5.4 The IoT Reference Architecture
192(9)
5.4.1 Smart City Communication Architecture
195(1)
5.4.2 Network Architectures for IoT Applications
196(1)
5.4.3 IP-Based Connectivity Models
197(4)
5.5 Prominent IoT Technologies
201(1)
5.6 The IoT: The Key Results
202(2)
5.7 The Advantages of the IoT Concept for Smart Cities
204(10)
5.7.1 The Co-Creation of IoT-Enabled Services for Smarter Cities
206(1)
5.7.2 Examples of IoT-Inspired Services Co-Created and Tested
206(1)
5.7.3 The Role of Advanced Sensing in Smart Cities
207(2)
5.7.4 Sensors Everywhere and in Everything
209(1)
5.7.5 Sensing as a Service for Cities of the Future
210(4)
5.7.5.1 Waste Management
211(1)
5.7.5.2 Smart Homes
212(1)
5.7.5.3 Smart Agriculture
212(1)
5.7.5.4 Environment Management
212(2)
5.7.5.5 Near-Field Communication
214(1)
5.8 Popular IoT/M2M Applications
214(7)
5.8.1 A Typical IoT Application
215(1)
5.8.2 Structural Health of Buildings
216(1)
5.8.3 Smart Energy
216(1)
5.8.4 Smart Healthcare
217(1)
5.8.5 Smart Home Security
217(1)
5.8.6 Smart Cargo Handling
217(1)
5.8.7 Smart Traffic Management
218(1)
5.8.8 Smart Inventory and Replenishment Management
218(1)
5.8.9 Smart Cash Payment
218(1)
5.8.10 Smart Tracking
218(1)
5.8.11 Smart Displays
219(1)
5.8.12 Smart Asset Management
219(1)
5.8.13 Air Quality
220(1)
5.8.14 Noise Monitoring
220(1)
5.8.15 Traffic Congestion
220(1)
5.8.16 Smart Parking
221(1)
5.9 Cyber Physical System for Smart City Needs
221(3)
5.9.1 CPS for Emergency Response
222(2)
5.10 Smart City Platforms and Frameworks
224(7)
5.10.1 A Communication Platform for Smart Cities
224(2)
5.10.2 A Smart City M2M Platform
226(1)
5.10.3 A Framework of Sensor-Cloud Integration
226(5)
5.11 Homeland Security and the Sensor Cloud
231(1)
5.12 Conclusion
232(1)
References
233(1)
Suggested Readings
233(2)
Chapter 6 Social Media Analytics For People Empowerment 235(30)
6.1 Introduction
236(3)
6.2 Building a Framework for the Use of Social Media Analytics for Business
239(13)
6.2.1 Social Media Content Metrics
241(1)
6.2.1.1 Content-to-Contact Ratio
241(1)
6.2.1.2 Comments-to-Content Ratio
241(1)
6.2.1.3 Comments-to-Profile Ratio
242(1)
6.2.1.4 Content-to-Share Ratio
242(1)
6.2.2 Different Dimensions of Social Media Analytics for Organizations
242(4)
6.2.2.1 Brand Advocacy and Brand Health Management
243(1)
6.2.2.2 Social Media Analytics to Calculate Net Promoter Score
243(1)
6.2.2.3 Optimize Marketing Communication Programs
244(1)
6.2.2.4 American Express Uses Social Media to Measure the Effectiveness of Their Campaigns
244(2)
6.2.3 Revenue and Sales Lead Generation
246(2)
6.2.4 Customer Relationship and Customer Experience Management
248(1)
6.2.4.1 Dell's Social Media Listening Command Center
248(1)
6.2.5 Innovation
249(1)
6.2.6 Social Media Tools
250(2)
6.2.6.1 Social Media Monitoring/Listening Tools
250(1)
6.2.6.2 Social Media Analytics Tools
251(1)
6.3 Social Media Analytics Architecture for Intelligent Cities
252(10)
6.3.1 Social Media Analytics for City Government
255(1)
6.3.2 Design of an Architecture for Sentiment Analysis in Intelligent Cities
255(4)
6.3.3 Use of IBM's Social Sentiment Index to Identify the Factors Impacting People in Five Canadian Cities
259(1)
6.3.4 Spain Uses Sentiment Analysis to Track and Improve Standards of City Services
260(1)
6.3.5 Sentiment Analysis to Track the Mood of City Residents
260(1)
6.3.6 FoodMood.in Uses Sentiment Analysis to Track Food Mood of Citizens
260(1)
6.3.7 Smart Policing Using Sensors and Domain Awareness System
261(1)
6.3.8 Case Study of Sentiment Analysis Implementation in an Intelligent City
261(1)
6.4 Conclusion
262(1)
References
263(2)
Chapter 7 Intelligent Cities: Strategy-Making And Governance 265(32)
7.1 Introduction
266(3)
7.2 IT Initiatives for Intelligent City Governance
269(12)
7.2.1 IT-Enabled City Strategies
272(1)
7.2.2 E-Government
272(5)
7.2.3 Key Challenges for E-Government
277(4)
7.2.3.1 Infrastructure Development
277(1)
7.2.3.2 Public Policy and Law
277(1)
7.2.3.3 Privacy
277(1)
7.2.3.4 Security
278(1)
7.2.3.5 Interoperability
278(1)
7.2.3.6 Public/Private Collaboration
278(3)
7.3 IT-Enabled Social Initiatives
281(5)
7.3.1 Urban Action Forums
281(5)
7.3.1.1 The Virtual Library Web Portal
282(1)
7.3.1.2 YourEdinburgh
282(1)
7.3.1.3 Library2Go
282(1)
7.3.1.4 Service Interfaces
282(1)
7.3.1.5 Hyper-Local Websites
283(1)
7.3.1.6 Support Networks
283(1)
7.3.1.7 Volunteering Networks
284(1)
7.3.1.8 Collective Action Forums
284(1)
7.3.1.9 Collective Action Forum-Pledgebank
284(1)
7.3.1.10 Carpooling Networks
285(1)
7.3.1.11 Use of Social Network Forums
285(1)
7.4 Ubiquitous or Intelligent City
286(7)
7.4.1 Ubiquitous Connectivity
286(1)
7.4.1.1 Network Broadband Infrastructure Development
287(1)
7.4.2 Omnipresent Devices
287(1)
7.4.3 Collaboration Platforms
287(1)
7.4.4 Cloud Computing
288(1)
7.4.4.1 Cloud Computing for Intelligent Cities
288(1)
7.4.5 Open Standards and Service-Oriented Architecture
288(1)
7.4.6 Geospatial Platforms
289(1)
7.4.7 Neogeography in U-Cities
289(1)
7.4.8 Internet of Things
290(1)
7.4.9 Advanced Analytics
291(1)
7.4.10 Open Access to Public Data
291(1)
7.4.11 Digitally Controlled Devices
292(1)
7.4.12 Social Media Networking
292(1)
7.5 Strategic Governance Framework for the Implementation of U-Cities
293(2)
7.5.1 City Objectives
293(1)
7.5.2 City Indicators
294(1)
7.5.3 City Components
294(1)
7.5.4 City Content
295(18)
7.5.4.1 First Ubiquitous City in the World
295(1)
7.6 Conclusion
295(1)
References
296(1)
Chapter 8 Smart Homes And Buildings 297(44)
8.1 Introduction
298(2)
8.2 Elucidating Technological Advancements
300(3)
8.3 Key Drivers for Smarter Homes and Buildings
303(1)
8.4 Prominent Use Cases of Smarter Homes and Buildings
304(1)
8.5 Smarter Homes and Building Elements
305(3)
8.6 Envisioning Smarter Homes and Buildings: The Role of the Cloud Theme
308(2)
8.7 Smarter Environments Are Instrumented, Interconnected, and Intelligent
310(1)
8.8 Smarter Home/Building Capabilities
311(2)
8.9 Smarter Home/Building Services in Clouds
313(9)
8.9.1 Benefits of Cloud-Enabled Smarter Homes
315(2)
8.9.2 Envisioning Service Delivery Platforms
317(3)
8.9.3 Building Management System
320(2)
8.10 IP-Based Convergence of Building Systems
322(3)
8.11 Smarter Homes: Architectural Styles, Patterns, and Approaches
325(3)
8.11.1 Smarter Homes-Middleware Platforms
328(1)
8.11.2 Smarter Home Frameworks
328(1)
8.12 Home Integration Standards: Industry Strength and Proprietary
328(8)
8.13 Conclusion
336(1)
Appendix
336(3)
References
339(2)
Chapter 9 Smart Energy, Utility, And Transport 341(38)
9.1 Introduction
342(1)
9.2 Smart Energy
343(11)
9.2.1 Smart Grids
345(2)
9.2.2 Energy Harvesting
347(1)
9.2.3 The Need for Big Data Analytics for Smarter Grids
348(3)
9.2.4 Envisioned Energy Grid Services for Smart Cities
351(3)
9.3 Smart Lighting
354(6)
9.3.1 Smart Lighting Approaches
354(4)
9.3.2 Wireless Lighting Control Systems
358(2)
9.4 Smart Transport
360(11)
9.4.1 Electric Vehicles
361(2)
9.4.2 Smarter Vehicles
363(1)
9.4.3 Technological Implications for Vehicles
364(3)
9.4.3.1 Insights-Driven Connected Vehicles
365(1)
9.4.3.2 Vehicle-to-Vehicle (V2V) Connectivity
365(1)
9.4.3.3 Vehicle-to-Cloud (V2C) Connectivity
365(2)
9.4.4 Vehicle Connectivity Platforms, Tools, and Applications
367(1)
9.4.5 Use Cases of Technology-Inspired Vehicles
368(1)
9.4.6 An Assortment of Vehicle-Centric Applications
369(2)
9.4.6.1 Knowledge Services
369(1)
9.4.6.2 Big Data Analytics for Smarter Transports
370(1)
9.5 Approaches for Smarter Transportation
371(4)
9.5.1 Predict Demand and Optimizing Capacity, Assets, and Infrastructure
372(1)
9.5.2 Improve the End-to-End Experience for Travelers
373(1)
9.5.3 Increase Operational Efficiency While Reducing the Environmental Impact
373(1)
9.5.4 Ensure Safety and Security
373(1)
9.5.5 Intelligent Transport Systems
374(1)
9.6 Smart Utilities
375(2)
9.6.1 Smart Metering
375(2)
9.7 Conclusion
377(1)
References
378(1)
Chapter 10 Intelligent Airports 379(32)
10.1 Introduction
380(3)
10.1.1 Inadequate Capacity
381(1)
10.1.2 Dissatisfied Passengers
382(1)
10.1.3 Increased Regulatory Requirements
382(1)
10.2 Evolution of Airport Infrastructure
383(1)
10.3 Airport 1.0
384(1)
10.4 Airport 2.0
384(19)
10.4.1 Personal Technology/Processes
386(4)
10.4.1.1 Mobile Applications for Airports
386(2)
10.4.1.2 Passenger Gait Mapping Using Augmented Vision Technology
388(1)
10.4.1.3 Social Media Applications in Airports
388(2)
10.4.2 Technology/Processes to Streamline the Passenger Journey
390(4)
10.4.2.1 Use of Biometrics in Airports
391(2)
10.4.2.2 RFID-Based Tracking of Baggage in Airports
393(1)
10.4.2.3 Quick Response Codes in Airports for Mobile Check-In
393(1)
10.4.2.4 Interactive Displays and Billboards in Airports
394(1)
10.4.3 Technology/Processes to Enhance Passenger Experience
394(5)
10.4.3.1 Inductive Charging of Electronic Devices
395(1)
10.4.3.2 Virtual Worlds and Interactive Surfaces
396(1)
10.4.3.3 Interactive Surfaces
397(2)
10.4.4 Processes for Increased Leisure Experience
399(2)
10.4.4.1 Finnish Sauna at Helsinki Airport
399(1)
10.4.4.2 Free Sightseeing Tour at Changi Airport, Singapore
399(1)
10.4.4.3 Free Cooking Classes at Paris Orly Airport
400(1)
10.4.4.4 Traditional Culture Workshops at Incheon Airport, South Korea
400(1)
10.4.5 IT for the Benefits of Passengers
401(2)
10.4.5.1 Cloud Computing
402(1)
10.4.5.2 Telepresence
402(1)
10.4.5.3 Wireless Broadband
403(1)
10.5 Envisioning Airports of the Future (Airport 3.0)
403(6)
10.5.1 Conceptual Models
404(1)
10.5.1.1 Independent City Model
404(1)
10.5.1.2 Extended City Model
404(1)
10.5.1.3 Transit Point Model
404(1)
10.5.2 Infrastructure Models
404(1)
10.5.2.1 Rented Assets Model
405(1)
10.5.2.2 Modular Model
405(1)
10.5.3 Revenue-Generating Models
405(1)
10.5.3.1 Generation of New Income Avenues
405(1)
10.5.3.2 Profit Redistribution
405(1)
10.5.3.3 Ecosystem Funding
406(1)
10.5.4 Public-Private Partnerships
406(1)
10.5.5 Technological Models
406(7)
10.5.5.1 Big Data and Predictive Analytics
407(1)
10.5.5.2 Internet of Things
407(1)
10.5.5.3 Genetic Profiling
408(1)
10.5.5.4 Biomimicry
408(1)
10.6 Conclusion
409(1)
References
410(1)
Chapter 11 Next-Generation Healthcare Systems 411(16)
11.1 Introduction
412(1)
11.2 Cloud Services in the Healthcare Sector
413(3)
11.2.1 Electronic Storage of Medical Records
414(1)
11.2.2 Office Productivity Solutions
414(1)
11.2.3 Health Information Exchange
415(1)
11.2.4 Collaboration Solution for Physicians
415(1)
11.2.5 Clinical Information System
415(1)
11.3 Big Data Analytics in Healthcare Sector
416(8)
11.3.1 Support Research in Genomics and Other Healthcare Projects
418(1)
11.3.2 Transform Data from Information
419(2)
11.3.2.1 Use of Explanatory Analytics by Predixion Software
420(1)
11.3.2.2 Use of Big Data by Health Fidelity
420(1)
11.3.3 Supporting Self-Care
421(1)
11.3.4 Support for Providers
421(1)
11.3.5 Increase Awareness
422(1)
11.3.5.1 Sproxil Uses Big Data to Identify Counterfeit Drugs
423(1)
11.3.5.2 Sickweather LLC Uses Social Media to Track Disease Outbreaks
423(1)
11.3.6 Pool Data to Build a Better Ecosystem
423(1)
11.4 Conclusion
424(1)
Reference
425(2)
Chapter 12 Security Management Of Intelligent Cities 427(30)
12.1 Introduction
428(1)
12.2 Security Requirements of an Intelligent City
428(5)
12.2.1 Confidentiality, Integrity, and Availability Triad
429(1)
12.2.2 Authentication, Authorization, and Audit Trial Framework
430(2)
12.2.3 Defense-in-Depth
432(1)
12.2.4 Trusted Computing Base
432(1)
12.2.5 Encryption
433(1)
12.3 Security Concerns of Cloud Platforms
433(9)
12.3.1 Virtual Machine Segmentation
434(1)
12.3.2 Database Segmentation
435(1)
12.3.3 VM Introspection
435(1)
12.3.4 Distributed Denial of Service
436(1)
12.3.4.1 Real-Life Example of DDoS Attack
436(1)
12.3.4.2 Imperva SecureSphere Web Application Firewall to Prevent DDoS Attacks
436(1)
12.3.5 VM/Hypervisor-Based Security Threats
437(1)
12.3.6 Unauthorized Alteration of VM Image Files
438(1)
12.3.7 VM Theft
439(1)
12.3.8 Inter-VM Attacks
439(1)
12.3.9 Instant-On Gaps
440(1)
12.3.10 Hyperjacking
441(1)
12.4 Security Threats to Big Data
442(3)
12.4.1 Distributed Programming Frameworks
443(1)
12.4.2 Use of NoSQL Databases
443(1)
12.4.3 Storage Tiering
443(1)
12.4.4 Data Source Validation
444(1)
12.4.5 Privacy Concerns
444(1)
12.4.5.1 Privacy Concern of Big Data Analysis
444(1)
12.5 Requirements of the Security Management Framework for Big Data
445(2)
12.5.1 Agile Scale-Out Infrastructure
445(1)
12.5.2 Security Analytics
446(5)
12.5.2.1 IBM Accelerator for Machine Data Analytics
446(1)
12.6 Threat Monitoring and Intelligence
447(1)
12.7 Security Threats in Smart Phones
447(2)
12.8 Security Solutions for Mobile Devices
449(1)
12.9 Security Concerns in the Internet of Things Platform
450(1)
12.10 Security Measures for IoT Platforms/Devices
451(2)
12.10.1 Secure Booting
451(1)
12.10.2 Mandatory Access Control Mechanisms
451(1)
12.10.3 Device Authentication for Networks
452(1)
12.10.4 Device-Specific Firewalls
452(1)
12.10.5 Controlled Mechanism to Ensure Application of Security Patches and Upgrades
452(1)
12.11 Security Threats to Different IT-Based Infrastructure Components of an Intelligent City
453(2)
12.11.1 Security Threats in Intelligent Transportation Systems
453(1)
12.11.1.1 Attack of a Public Transport System in Europe
454(1)
12.11.2 Security Threats in Intelligent/Smart Grids and Other Infrastructure Components of an Intelligent City
454(1)
12.12 Best Practices to Be Adopted for a Secure Intelligent City
455(1)
12.13 Conclusion
456(1)
References
456(1)
Index 457
Pethuru Raj PhD has been working as a cloud infrastructure architect in the IBM Global Cloud Center of Excellence, IBM India Bangalore. Previously he worked as TOGAF-certified enterprise architecture consultant in Wipro Consulting Services Division, Bangalore. He also had a fruitful stint as a lead architect in the corporate research division of Robert Bosch, India. He has gained thirteen years of IT industry experience.

Dr. Raj finished the CSIR-sponsored PhD degree in Anna University, Chennai, and continued the UGC-sponsored postdoctoral research in the department of Computer Science and Automation, Indian Institute of Science, Bangalore until 1999. Thereafter, he was granted a couple of international research fellowships (JSPS and JST) to work as a research scientist for three years in two leading Japanese universities. His technical competencies lie in service oriented architecture, cloud computing, enterprise architecture, context-aware computing and machine-to-machine integration, Big Data Analytics, Smart Cities, and business integration methods.

He has contributed book chapters for a number of high-quality technology books edited by internationally acclaimed professors and professionals. The CRC Press, USA, released his first book titled Cloud Enterprise Architecture in 2012. He has edited a book on the title Cloud Infrastructures for Big Data Analytics. He maintains an Information Technology (IT) portal at www.peterindia.net Anupama Raman is currently working as Content Lead for Smart Cities Brand of IBM and she is a part of Software group, Industry Solutions of IBM India. Prior to this, she was working with EMC Data Storage. She is a certified Storage Area Networking expert and is also a certified Data Center Architect. She is also certified in Cloud infrastructure and Services Management. Apart from these technical certifications, in the field of writing. She is a certified Information mapping professional and in the field of project management, she is a certified Scrum master. She holds an M.Tech degree in Computer Science and Engineering and is currently pursuing an MBA in IT Management. She has presented and published over twenty research papers in various national and international conferences and she has also written numerous book chapters with various national and international publishers.
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